Methods for assessment of Rey Auditory Verbal Learning Test performance in memory clinic patients and healthy adults - at the cross-roads of learning theory and clinical utility
Bibliographic record
Abstract
Background: Knowledge is still lacking regarding the preferred method for evaluation of learning in the Rey Auditory Verbal Learning Test (RAVLT). Validity of different methods was examined by the effect size in differentiating diagnostic stages in memory clinic patients versus healthy adults and the strength of association between RAVLT performance and brain atrophy. Method: The study included individuals with dementia (n = 247), Mild Cognitive Impairment (MCI, n = 709), Subjective Cognitive Impairment (SCI, n = 175) and cognitively unimpaired adults serving as healthy controls (HC, n = 102). All patients went through a comprehensive clinical examination and neuropsychological assessment of cognition including episodic memory gauged with RAVLT and brain imaging of medial temporal atrophy, cortical atrophy, and white matter hyperintensity. Results: The standard method for evaluation of learning in RAVLT (summed score over five trials) together with the late learning method (mean of trials 4 and 5) were the two most powerful methods according to group differentiation (discriminant validity). Both methods also showed considerable association with medial temporal atrophy (construct validity). The initial RAVLT performance represented by results on trial 1 and the constant in regression analysis with the power function provided information regarding attention that was important for the separation of SCI and HC. Conclusions: The most favorable clinical utility was indicated by discriminant and construct validity by total learning (standard method) including both attention- and learning-related parts and late learning of RAVLT performance, while theoretical understanding of mental processes involved in RAVLT performance was provided by the distinction between initial versus the subsequent learning performance.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.016 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.004 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".